Consider the following data for the next three (03) items that follow : There are 90 applicants for a job. Some of them are graduates. Some of them have less than three years experience. Let G be the event that the first applicant interviewed is a graduate and T be the event that first applicant interviewed has at least 3 years experience.Number of graduates Number of non-graduates At least 3 years experience 18 9 Less than 3 years experience 36 27
What is \(P (G \cap \overline T)\) equal to?
The problem provides data about 90 job applicants, categorized by whether they are graduates and their years of experience. We are given the following data in a table format:
| At least 3 years experience (T) | Less than 3 years experience (\(\overline T\)) | Total | |
|---|---|---|---|
| Number of graduates (G) | 18 | 36 | 54 |
| Number of non-graduates (\(\overline G\)) | 9 | 27 | 36 |
| Total | 27 | 63 | 90 |
We are asked to find the probability \(P(G \cap \overline T)\). This represents the probability that the first applicant interviewed is a graduate (event G) AND has less than 3 years experience (event \(\overline T\)). The symbol \(\cap\) denotes the intersection of the events, meaning both events occur.
The term \(G \cap \overline T\) refers to the set of applicants who are both graduates and have less than 3 years of experience. Looking at the provided table:
From the table, the number of graduates with less than 3 years experience is 36.
The probability of an event is calculated as the ratio of the number of favorable outcomes to the total number of possible outcomes.
In this case:
The probability \(P(G \cap \overline T)\) is therefore:
\(P(G \cap \overline T) = \frac{\text{Number of graduates with less than 3 years experience}}{\text{Total number of applicants}}\)
\(P(G \cap \overline T) = \frac{36}{90}\)
To simplify the fraction \(\frac{36}{90}\), we can find the greatest common divisor (GCD) of 36 and 90, or simply divide by common factors:
So, \(P(G \cap \overline T) = \frac{2}{5}\).
The probability that the first applicant interviewed is a graduate and has less than 3 years experience is \(\frac{2}{5}\).
| Event | Description | Number of Applicants | Probability (Number/90) |
|---|---|---|---|
| G | Graduate | 54 | \(\frac{54}{90} = \frac{3}{5}\) |
| \(\overline G\) | Non-graduate | 36 | \(\frac{36}{90} = \frac{2}{5}\) |
| T | At least 3 years experience | 27 | \(\frac{27}{90} = \frac{3}{10}\) |
| \(\overline T\) | Less than 3 years experience | 63 | \(\frac{63}{90} = \frac{7}{10}\) |
| \(G \cap T\) | Graduate and At least 3 years experience | 18 | \(\frac{18}{90} = \frac{1}{5}\) |
| \(G \cap \overline T\) | Graduate and Less than 3 years experience | 36 | \(\frac{36}{90} = \frac{2}{5}\) |
| \(\overline G \cap T\) | Non-graduate and At least 3 years experience | 9 | \(\frac{9}{90} = \frac{1}{10}\) |
| \(\overline G \cap \overline T\) | Non-graduate and Less than 3 years experience | 27 | \(\frac{27}{90} = \frac{3}{10}\) |
The table provided is a type of contingency table, specifically a 2x2 table, used to display the frequency distribution of two variables (in this case, Graduate Status and Experience). Such tables are very useful in calculating probabilities, especially joint probabilities and marginal probabilities.
Understanding how to read and use contingency tables is fundamental for solving probability problems involving two or more categorical variables.
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